Bibliographic record
Abstract
Restitution scholars are almost unanimous in rejecting the term quasi‐contract. This essay challenges this view. It begins by demonstrating that many debates among restitution scholars are in fact debates about the boundaries of consent‐based liability. This serves as an introduction to the main thesis advanced, which is that the idea of quasi‐contract, which is supposed to cover cases in which the parties would have made a contract if conditions allowed them to do so, helps to explain the doctrine better than the conclusory language of unjust enrichment. The essay concludes by situating the argument within the growing literature on the normative foundations of restitution. It argues that quasi‐contractual liability should be understood not as part of unjust enrichment, but as a different basis of liability that can help us see what liability for unjust enrichment might be: liability grounded in notions of fairness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.045 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".